Technology

We come from the school of thought that it is more pragmatic and scalable to build simple heterogeneous robots that focus on a smaller subset of tasks and coordinate these robots to achieve larger objectives, instead of building all-in-one complex robots. We focus on the following technologies to create value for our customers.

Award-Winning Distributed Intelligence

Robots come in all shapes and sizes to execute a fixed set of tasks in a relatively optimal manner compared to people. In order to remain flexible the robotics solutions should be able to mix and match heterogeneous robots such that each robot is executing the set of tasks it is designed for, accommodate different business processes and environments and handle uncertainty coming from collaborating with people.

RR has patented multiple technologies in the domain of multi-robot planning and control and is also the maintainer and lead contributor of ALICA, a state-of-the-art open source framework multi-robot coordination and control.

ALICA on GitHub. The development of this technology is supported by the Tokyo Metropolitan Government’s Innovation Tokyo Project with USD 5 mil. in subsidies.

Award-Winning Distributed Intelligence

Robots come in all shapes and sizes to execute a fixed set of tasks in a relatively optimal manner compared to people. In order to remain flexible the robotics solutions should be able to mix and match heterogeneous robots such that each robot is executing the set of tasks it is designed for, accommodate different business processes and environments and handle uncertainty coming from collaborating with people.

RR has patented multiple technologies in the domain of multi-robot planning and control and is also the maintainer and lead contributor of ALICA, a state-of-the-art open source framework multi-robot coordination and control.

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ALICA on GitHub. The development of this technology is supported by the Tokyo Metropolitan Government’s Innovation Tokyo Project with USD 5 mil. in subsidies.

Motion Planning and Control

Motion Planning and Control focuses on pushing the agility of a single robot while keeping the stability. Being agile helps robots to be able to handle a wide variety of uncertainties e.g.,  handle dynamic obstacles such as people, carts, and other robots.

Rapyuta Robotics has patented multiple technologies in the domain and has been the pioneer in pushing the boundaries of pushing the physical limits of robots from drones to jumping cubes.

The Cubli

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Autonomous Drones

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Motion Planning and Control

Motion Planning and Control focuses on pushing the agility of a single robot while keeping the stability. Being agile helps robots to be able to handle a wide variety of uncertainties e.g.,  handle dynamic obstacles such as people, carts, and other robots.

Rapyuta Robotics has patented multiple technologies in the domain and has been the pioneer in pushing the boundaries of pushing the physical limits of robots from drones to jumping cubes.

The Cubli

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Autonomous Drones

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Cloud-Native Robotics DevOps Platform

‘Software is eating the world’ – Marc Andreessen. This holds for robotics too. For the last two decades, software was mostly embedded, secondary, and had the same lifecycle as the hardware. However, software now – thanks to increased computation, better networks, and cloud computing, machine learning breakthroughs – is moving to the main stage. Compared to the install and forget mindset of the embedded software, the new physically-distributed,  constantly-updated, large software stacks require a completely new mindset and infrastructure to manage. 

Our founding team worked on RoboEarth, an EU FP7 project (EUR 5.7 mil.) that pioneered  an internet for robots. 

Prior work:

Mohanarajah, D. Hunziker, R. D’Andrea and M. Waibel, “Rapyuta: A Cloud Robotics Platform,” in IEEE Transactions on Automation Science and Engineering, vol. 12, no. 2, pp. 481-493, April 2015, doi: 10.1109/TASE.2014.2329556.

Rapyuta: A Cloud Robotics Framework

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Rapyuta: A Cloud Robotics Framework

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Cloud-Native Robotics DevOps Platform

‘Software is eating the world’ – Marc Andreessen. This holds for robotics too. For the last two decades, software was mostly embedded, secondary, and had the same lifecycle as the hardware. However, software now – thanks to increased computation, better networks, and cloud computing, machine learning breakthroughs – is moving to the main stage. Compared to the install and forget mindset of the embedded software, the new physically-distributed,  constantly-updated, large software stacks require a completely new mindset and infrastructure to manage. 

Our founding team worked on RoboEarth, an EU FP7 project (EUR 5.7 mil.) that pioneered  an internet for robots. 

Prior work:

Mohanarajah, D. Hunziker, R. D’Andrea and M. Waibel, “Rapyuta: A Cloud Robotics Platform,” in IEEE Transactions on Automation Science and Engineering, vol. 12, no. 2, pp. 481-493, April 2015, doi: 10.1109/TASE.2014.2329556.

Rapyuta: A Cloud Robotics Framework

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Cloud-based Collaborative 3D Mapping in Real-Time with Low-Cost Robots

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Award-Winning Perception

Having a better understanding of the surrounding environment enables a robot to intelligently choose the best action to optimize the outcome of the tasks. The perception functionality should be able to identify (categorize) and estimate the pose of a wide variety of objects with sufficient accuracy and precision to guarantee safe and intelligent actions.

We won the Intel OpenCV award held globally amongst 235 teams. We have developed specialized spatial AI vision systems and novel algorithms that are best adopted to work in challenging and dynamic environments.

The development of this technology is supported by the NEDO, Japan with USD 1.6 mil. in subsidies.

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Award-Winning Perception

Having a better understanding of the surrounding environment enables a robot to intelligently choose the best action to optimize the outcome of the tasks. The perception functionality should be able to identify (categorize) and estimate the pose of a wide variety of objects with sufficient accuracy and precision to guarantee safe and intelligent actions.

We won the Intel OpenCV award held globally amongst 235 teams. We have developed specialized spatial AI vision systems and novel algorithms that are best adopted to work in challenging and dynamic environments.

The development of this technology is supported by the NEDO, Japan with USD 1.6 mil. in subsidies.

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Large-Scale Simulation

It is not always obvious which type of robots will be the best fit to solve a given business process. Given robot hardware is relatively expensive and has long lead times, prototyping with real robots is not the best option. Simulation provides a low-cost alternative for prototyping. Rapyuta Robotics’ large-scale simulation allows the business to evaluate multiple options to choose the best solution and easily build realistic environments and accurately predict the return on investments.

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In order to leverage the knowledge and tooling of the gaming industry, we build on top of Unreal engine, an industry leading game engine.

rclUE on our blog
rclUE on GitHub
The development of this technology is supported by the Tokyo Metropolitan Government’s Innovation Tokyo Project with USD 5 mil. in subsidies.

Large-Scale Simulation

It is not always obvious which type of robots will be the best fit to solve a given business process. Given robot hardware is relatively expensive and has long lead times, prototyping with real robots is not the best option. Simulation provides a low-cost alternative for prototyping. Rapyuta Robotics’ large-scale simulation allows the business to evaluate multiple options to choose the best solution and easily build realistic environments and accurately predict the return on investments.

Play Video

In order to leverage the knowledge and tooling of the gaming industry, we build on top of Unreal engine, an industry leading game engine.

rclUE on our blog
rclUE on GitHub
The development of this technology is supported by the Tokyo Metropolitan Government’s Innovation Tokyo Project with USD 5 mil. in subsidies.